package com.atguigu.flink0624.chapter11;

import com.atguigu.flink0624.bean.WaterSensor;
import org.apache.flink.api.common.eventtime.WatermarkStrategy;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;

import java.time.Duration;

import static org.apache.flink.table.api.Expressions.$;

/**
 * @Author lizhenchao@atguigu.cn
 * @Date 2021/11/19 10:26
 */
public class Flink13_Window_Over_1 {
    public static void main(String[] args) throws Exception {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);
        
        DataStream<WaterSensor> waterSensorStream =
            env
                .fromElements(new WaterSensor("sensor_1", 1000L, 10),
                              new WaterSensor("sensor_1", 4000L, 20),
                              new WaterSensor("sensor_1", 4000L, 40),
                              new WaterSensor("sensor_1", 5000L, 50),
                              new WaterSensor("sensor_2", 3000L, 30),
                              new WaterSensor("sensor_2", 6000L, 60))
                .assignTimestampsAndWatermarks(
                    WatermarkStrategy
                        .<WaterSensor>forBoundedOutOfOrderness(Duration.ofSeconds(3))
                        .withTimestampAssigner((ws, ts) -> ws.getTs())
                );
        
        StreamTableEnvironment tenv = StreamTableEnvironment.create(env);
        
        Table table = tenv.fromDataStream(waterSensorStream, $("id"), $("ts").rowtime(), $("vc"));
        tenv.createTemporaryView("sensor", table);
        
        /*tenv
            .sqlQuery("select " +
                          "id, " +
                          "ts, " +
                          "vc, " +
                          //                          "sum(vc) over(partition by id order by ts rows between unbounded preceding  and current row)" +
                          //                          "sum(vc) over(partition by id order by ts rows between 1 preceding  and current row)" +
//                          "sum(vc) over(partition by id order by ts range between unbounded preceding  and current row) " +
                          "sum(vc) over(partition by id order by ts range between interval '3' second preceding  and current row) " +
                          "from sensor")
            .execute()
            .print();*/
        
        tenv
            .sqlQuery("select " +
                          "id, " +
                          "ts, " +
                          "vc, " +
                          "sum(vc) over w, " +
                          "max(vc) over w, " +
                          "min(vc) over w " +
                          "from sensor " +
                          "window w as (partition by id order by ts rows between unbounded preceding  and current row)")
            .execute()
            .print();
        
    }
}
